Abstract
Intricate data processing, reliable and quick message exchanges are the primary requirements to actualize the next-generation vehicular network applications in smart cities. The cellular macro base stations and IEEE 802.11p based WAVE technology can offer data connectivity to low mobility users but fails to support the high data rate and low latency requirement for next-generation vehicular network applications. The mmWave beam antennas, along with the edge computing technique of the 5G ecosystem, is capable of supporting such a service demands. Therefore RSUs equipped with mmWave beam antennas can be a pragmatic solution to this problem. However, the cost-efficient deployment of mmWave enabled 5 G RSUs on a smart city under a restricted budget presents a significant challenge. We address this issue by formulating it as a Budgeted Maximum Coverage optimization to place such 5G RSUs in an urban vehicular scenario efficiently. The optimization maximizes the long term profits under the constraint of a limited budget. The problem under consideration is an NP-hard problem. Therefore, we employ two approximation algorithms. The greedy algorithm is fast and guarantees $\frac{1}{2}\left(1-\frac{1}{e}\right)$ approximation. The modified-greedy algorithm is slower but guarantees $\left(1-\frac{1}{e}\right)$ approximation. We validate the performance of our proposed scheme in an urban city with real data.
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